Track finite packed SFT datasets and metrics

[tylerpoon]

• I, the PR author, have personally reviewed every line of this PR.

What does this PR do?

Track finite packed SFT dataset progress using actual sample counts, configure token- versus microbatch-weighted loss reporting, and update progress/throughput accounting. Include distributed-semantics regression tests.

This is part of a review-split multimodal SFT series. Production run scripts, data YAMLs, checkpoint conversion tooling, and separate CI compatibility fixes are outside this series.

Dependencies and review scope

Targets main.

Validation

• Replayed onto public main at 46fb90ca942a2950c58c5654b3e56877e88a3e35, preserving atomic signed and signed-off commits.
• The original combined feature stack had multi-node Super SFT validation before this migration; that is not an isolated-PR or rebased-head test result.
• GitHub CI is pending. No GPU tests have been rerun locally for these rebased heads.
• Local Black, isort, pylint, and Ruff checks passed for paths covered by the repository autoformat script (megatron/core and tests). Mypy is unavailable locally. Changed Python files pass syntax parsing; no CI configuration changes are included.

Kept as a draft pending CI and dependency integration.

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[tylerpoon]

/ok to test e66b9e5